Applied Scientist — Live Data & Causal Analytics

Amazon Inc.; Seattle (WA); On-site; USD 143,000 - 193,000; Full time

Job summary

Amazon Live Data Engineering, Sciences and Analytics (DESA) is seeking an Applied Scientist to design production-grade models, experiments, and signals for causal measurement and content intelligence. You will own problems end-to-end—from framing the research question through model deployment and A/B experimentation—collaborating with Data Engineers and a business intelligence partner.

You will influence how brands invest and how customers discover content by delivering ranking signals and

Qualifications

• PhD or Master with 4+ years CS/CE/ML experience
• Proficient in Java, C++, Python
• Experience with PyTorch or JAX and ML lifecycles
• Experience with A/B testing and audience segmentation
• Experience with large-scale distributed systems (Hadoop, Spark)
• Experience with causal inference methods (incrementality, dif-in-diff, IV, synthetic control)

Responsibilities

• Design and deploy causal attribution models (incrementality testing, multi-touch)
• Build brand lifecycle and campaign optimization models at scale
• Design and run A/B experiments for new product surfaces and ranking changes
• Develop multimodal and generative models for content intelligence
• Own full ML lifecycle from research to production deployment and monitoring
• Present findings to senior leadership and partner teams
• Contribute to internal publications and cross-team methodology sharing

Skills

Modeling for business applications

A/B testing

Causal inference

Production deployment

Education

PhD

Masters in CS/CE/ML

Tools

Java

C++

Python

PyTorch

JAX

Hadoop

Spark

Bedrock

SageMaker

Redshift

Job description

Amazon Live Data Engineering, Sciences and Analytics (DESA) is seeking an Applied Scientist to design production-grade models, experiments, and signals for causal measurement and content intelligence. You will own problems end-to-end—from framing the research question through model deployment and A/B experimentation—collaborating with Data Engineers and a business intelligence partner.

You will influence how brands invest and how customers discover content by delivering ranking signals and